Integrating Insights

Digital pathology sits at the heart of explainable AI in healthcare. As pathologists bridge the gap between digital imaging data and clinical interpretation, their expertise ensures AI tools remain accountable and trusted in medical practice

Enhancing Outcomes

  • Pathologists are navigating transition from traditional microscopy to digital whole slide image (WSI) analyis.

  • Digitization of patient samples is the foundation of explainability in AI.

  • The initial step in ensuring transparency and interpretability in AI-driven diagnostics begins with patient images and their data.

  • Convolutional Neural Network; CNN; Gleason Grade; Heat map; prostate cancer; prostate cancer staging;

    Driving these diagnostics are image analysis (IA) algorithms derived from deep learning (DL) networks.

    These sophisticated algorithms are crafted from a comprehensive array of WSIs and associated metadata sourced from the laboratory.

  • heatmap

    A shared language bridges medical expertise and technological innovation.

    Development must involve collaborative inputs from both pathologists and engineers.

  • Pathologists must adopt many domains

    Computer vision, operations expertise, and data science are among many. Beyond traditional training, interdisciplinary collaboration is required to effectively manage and interpret vast datasets, develop AI, and ensuring the responsible implementation of technology in clinical practice.

  • heat map, WSI, whole slide image

    Multimodal biological data is being infused in technology-enabled clinical and research workflows throughout the globe.

    Pathologists are adopting new roles as bioinformaticians and computer visionaries of advanced medical solutions, bridging the clinical-computational divide to better patient care.

  • Digital pathology data is central to AI development, but whole slide images (WSI) pose significant storage and operational challenges. Pathologists expertise is essential in optimizing data compression, cloud storage, and retrieval systems.

  • Average weight of a humpback whale = approximate volume of traditional Hollerith “punch” cards needed to store 1gb of WSI data

  • 2x the weight of the International Space Station (ISS) = the average volume of glass slides handled yearly at major academic medical centers, large regional hospitals, and specialized reference laboratories serving multiple healthcare facilities

  • Data requirements for storing cumulative (new and archival) WSI data at a high-volume, fully digitized academic medical center (in PB) = approximately 20x the total storage capacity of typical major streaming service providers (Netflix, Amazon Prime Video, Hulu, etc.)

  • Successful laboratory digitization requires close collaboration between pathologists and IT specialists. By aligning technological infrastructure with clinical workflows, we ensure efficient, sustainable systems that enhance diagnostic capabilities.

Pathologists are the stewards of laboratory data, establishing diagnostic ground truth for AI model validation. With 70% of medical decisions driven by laboratory diagnostics, pathologists' expertise forms the foundation of explainable AI. While current AI solutions focus on imaging, the future lies in integrating broader laboratory data.